Self-training. Self-training has been widely investigated in semi-supervised learning [1]}, [2]}, [3]}, [4]}, [5]}, [6]}.
[rgb]0,0,0Self-training methods increase labeled data via pseudo label generation on unlabeled data to leverage the information on both labeled and unlabeled data. [rgb]0,0,0Recent deep self-training involves representation learning of the feature encoder and classifier refinement, mostly adopted in semi-supervised learning [2]} and domain adaptation [8]}, [6]}. 
[rgb]0,0,0In unsupervised VAD, Pang et al. [10]} introduced a self-training framework deployed on the testing video directly, assuming the existence of an anomaly in the given video.
